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Titlebook: Model Averaging; David Fletcher Book 2018 The Author(s), under exclusive licence to Springer-Verlag GmbH, DE, part of Springer Nature 2018

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發(fā)表于 2025-3-21 20:09:22 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Model Averaging
編輯David Fletcher
視頻videohttp://file.papertrans.cn/636/635714/635714.mp4
概述Provides an overview of current model averaging methods, with an emphasis on applications.Compares the frequentist and Bayesian approaches to model averaging.Includes an extensive list of references a
叢書名稱SpringerBriefs in Statistics
圖書封面Titlebook: Model Averaging;  David Fletcher Book 2018 The Author(s), under exclusive licence to Springer-Verlag GmbH, DE, part of Springer Nature 2018
描述.This book provides a concise and accessible overview of model averaging, with a focus on applications. Model averaging is a common means of allowing for model uncertainty when analysing data, and has been used in a wide range of application areas, such as ecology, econometrics, meteorology and pharmacology. The book presents an overview of the methods developed in this area, illustrating many of them with examples from the life sciences involving real-world data. It also includes an extensive list of references and suggestions for further research. Further, it clearly demonstrates the links between the methods developed in statistics, econometrics and machine learning, as well as the connection between the Bayesian and frequentist approaches to model averaging. The book appeals to statisticians and scientists interested in what methods are available, how they differ and what is known about their properties. It is assumed that readers are familiar with the basic concepts of statistical theory and modelling, including probability, likelihood and generalized linear models..
出版日期Book 2018
關(guān)鍵詞Model averaging; Bayesian Modeling; Frequentist Model Averaging; Mixed models; Posterior model probabili
版次1
doihttps://doi.org/10.1007/978-3-662-58541-2
isbn_softcover978-3-662-58540-5
isbn_ebook978-3-662-58541-2Series ISSN 2191-544X Series E-ISSN 2191-5458
issn_series 2191-544X
copyrightThe Author(s), under exclusive licence to Springer-Verlag GmbH, DE, part of Springer Nature 2018
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978-3-662-58540-5The Author(s), under exclusive licence to Springer-Verlag GmbH, DE, part of Springer Nature 2018
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https://doi.org/10.1007/978-3-662-58541-2Model averaging; Bayesian Modeling; Frequentist Model Averaging; Mixed models; Posterior model probabili
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2191-544X methods are available, how they differ and what is known about their properties. It is assumed that readers are familiar with the basic concepts of statistical theory and modelling, including probability, likelihood and generalized linear models..978-3-662-58540-5978-3-662-58541-2Series ISSN 2191-544X Series E-ISSN 2191-5458
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Book 2018es to model averaging. The book appeals to statisticians and scientists interested in what methods are available, how they differ and what is known about their properties. It is assumed that readers are familiar with the basic concepts of statistical theory and modelling, including probability, likelihood and generalized linear models..
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Agent-Based Adaptive Production Scheduling — A Study on Cooperative-Competition in Federated Agent Ant a simple auction mechanism at each processing center and a global reinforcement learning mechanism to minimize cost contents in the system. Results of simulations using the cooperative-competition approach and the strictly competitive model are presented. Simulation results show that there were i
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